Mehrstufiges multikriterielles Job-Shop-Scheduling*/Multi-Stage and Multi-Criterial Job-Shop-Scheduling

Energiepolitische Veränderungen erhöhen den Druck auf Produktionsunternehmen, erneuerbare Energiequellen zu nutzen. Deren Einbindung erfordert die Entwicklung neuer Ansätze zur Produktionsplanung und -steuerung (PPS). Dazu wird ein mehrstufiges simulationsbasiertes Verfahren für ein reales Job-Shop-Problem vorgeschlagen, welches die Shifting-Bottleneck-Heuristik zur Findung einer kundenorientierten Ausgangslösung auf Basis des prognostizierten Energieangebots nutzt. Vom resultierenden Lastprofil ausgehend wird eine Feinterminierung zur Optimierung von Lastspitzen unter Beachtung der Ergebnisse der Vorplanung durchgeführt. Auswirkungen kurzfristiger stochastischer Einflüsse werden überdies durch intelligente Produktionssteuerung, aber auch durch aktives Energie- und Lastmanagement kompensiert. Im vorliegenden Beitrag werden für das Anwendungsszenario Flexibilitätspotentiale abgeleitet und das Konzept des „ZIEL“-Systems erläutert. Darüber hinaus wird der aktuelle Bearbeitungsstand abgegrenzt und weiterführende Arbeiten vorgestellt.   Taking responsibility for a sustained energy policy the industry is more and more forced to enhance their engagement in the use of renewable energy. To go beyond energy efficient equipment new approaches in production planning and control tailored to meet both economic and ecological goals are needed. Hence, a multistage simulation based procedure for a real-life oriented job shop production scenario is proposed. It combines a modified version of the Shifting Bottleneck Heuristic for gaining a production plan with energy supply constraints and a sophisticated energy simulation with Matlab Simulink. Short-term and stochastic effects are tackled with suited production control strategies as well as active energy- and load-management. In this paper flexibility options for the use case are derived and the concept of the „ZIEL“ system explained. The current work and the ongoing research are shown.

Scheduling method of robotic cells with machine–robot process and time window constraints

Robotic cells are widely used in the fields of incorporate automation and repetitive processing. Throughput analysis and scheduling of robotic cells with machine process have been well studied, while research work on robotic cells with machine–robot process in which robots concurrently perform collaborated tasks in addition to part transportation is still at an early stage. After defining the concepts of internal and external time window constraints, we propose a robotic cell scheduling problem with machine process and machine–robot process simultaneously, when processing time window is an essential constraint. According to the constraints in real engineering practice, a mathematic model of single-gripper robotic cells is established to minimize the average manufacturing cycle time. A shifting bottleneck searching algorithm is proposed based on the basis of analyses. In addition, a lower bound for the average manufacturing cycle time is established. Finally, through extensive simulation experiments, the numerical and experimental results demonstrate that the shifting bottleneck searching provides optimal or near optimal solutions.

A Review on Strategic Positioning of Bottleneck around the Customer Order Decoupling Point and Issues on Production Planning in Supply Chain

The decoupling point separates part of the supply chain oriented towards customer orders from the part based on forecast planning. This paper focuses on identification of bottlenecks and their positioning with respect to customer order decoupling point (CODP) in supply chain continuum. The research is based on a conceptual model that separates engineer to order (ETO), make to order (MTO), assemble to order (ATO) and make to stock (MTS) by a decoupling point. The important feature of this paper is that supply, demand and operational constraints are allocated in specific part of the supply chain, making it more versatile. Shifting bottleneck concepts, including impact of bottleneck position and issues concerning production and capacity planning, are studied extensively to stabilize the supply chain and reduce its complexity.